Welcome to top 10 topic number 10 witches, the distinction between qualitative variables of quantitative variables to and the calm top 10 topic is understanding what types of statistical analyses are appropriate for use on qualitative data as compared to the types of analysis that are appropriate for use on qualitative excuse me on quantitative data, so if you're at the business or a two page click on exam review of then click on statistics review click on statistics review for the PowerPoint presentation and will give it a second here to come out and I will call over this with you and narrate the PowerPoint slides for it and I'll also add a little bit of information as well to cocaine and Wilson navigate down here to slide about 50 to, which is the material excuse for a ticket to further on down is on slide number 104. Now remember what you are trying to do in qualitative means mostly about words, whereas quantitative means mostly about numbers. There are levels of measures that in day to the lowest level are qualitative data. Sometimes it's called nominal data or better categorical data, and obviously some examples of those in a moment higher orders of data above nominal data are ordinal data which are numbers that are peer into in order are usually these calm from a survey like a light for scale, where you're asked to do strongly agree agree new troll disagreed strongly disagree those of ordinal numbers and then higher still are in overall and ratio numbers so the lowest slow for qualitative data, all sometimes called categorical data and higher up for quantitative pickle ordinal and interval and ratio data in a role is so a typical of a real number will get to those in a moment that can do things number second always be divided and ratio is is like an integral number but also has a true user of those distinctions are then important now. But the reach of reason, this is a top 10 concept is because the types of analyses that you do with the lower-level data qualitative data is different than the types of analysis you do with higher-level data of the quantitative are paying so switching to the next slide slide 105 with start with a lower level data qualitative data. The PowerPoint slide calls as categorical data in which this is data will where you have to put them into a category success versus LA or deafness of the marital status color suit coat and a four star hotel and tour guides them to give you another example. Gender genders either male or female, there is no such thing as taking the average between male and female doesn't make any sense. And all you can do is count up the number of individuals in each one of those categories successful versus Faler count up the number of successes count up the number of failures, and deafness of the black white Chicano Asian-American eccentric century have to count up the number of individuals so sometimes this is called Count global data and Merrillville status as well and as well as all the others in pain and give you one missed on this list say you had to do a survey of a of whether or not, what types of Coca-Cola is that people like so another kind a categorical data would be a type of Coca-Cola can be Coke, Pepsi, RC. Etc. etc. so there's there's really no way to take an average or mean or standard deviation with that there are some kinds of analyses like chi-squared in other words is the data independent Palm. But he can't do exactly the same kinds of things she can do with higher-order data where you can measure it with inner false to think.
A so for example qualitative data if he needed average, which is the mean or the arithmetic mean you keep can't calculate that that's the first bullet. There is no way to calculate average gender you're one or the other male or female and a second bullet however, you can compute the mode of average person is married buys a blue car made in America or remember will talk about the different kinds of measures of central tendency and next section, but the mode is the most popular of the most common category so of the mode. You can have more married people than single, so we were say the modus marriage and a moving up to scale to quantitative data. There are two kinds of quantitative data, discrete and continuous and will talk a little bit more about them in a moment discreet means individual steps and pain that better measured in chunks that have very sharp and start points and points 1234567 is supposed to continuous data we can always split further the mean of two and three is 2.5. The mean of two and 2.5 is 2.25 etc. etc. there are no distinct parts of talk more about that in a moment status. Here's some examples on slide one away of this of the PowerPoint presentation of discrete value as integer values 012 example is the binomial by means to a binomial is. A probability distribution are us and a set of random variables that follow the binomial function on number three is a finite number. Possible values use counting the number force counting I told you that and sometimes their account level date are two different kinds of tallies and a number of the men more discrete data number of Brothers number of cars arriving at a gas station and tank continuous data are real numbers such as decimal values such as the doll such as $22.22 and other kinds of continuous data for example is the NT is seen. It is, the upper KC is the standard normal distribution, will we convert the population of values into a standardized a score from a raw score to the standard_NT issue, and she recall is the is a distribution that we use when we're doing hypothesis test for the other continuous is our infinite number of possible values is remember like my division between two and three and two and 2.5 you can always divide it more miles per gallon distance to rations of time why durations of times because you could always split up the time between days or hours minutes seconds millisecond success for such okay, what types of slight 110 what types of graphical tools do we use with different kinds of data we use a pie chart or bar chart with qualitative data. High church and not necessarily recommended you can use them, but humans don't do too well with a pie chart to hard their hard for humans to figure out the area of a slice of a pious to try and stick with a bar chart, which is sometimes called a column chart as well with with Colin or data and you probably seen plenty of this kind of data to. You can also use a joint frequency table, which is qualitative data relates for example marital status verses of code on that particular case use a table. Not a diagram not in our graphics and on and on and I are on the graphical artifacts and for example in marital status versus the code 1 of the war a column with the zip code for example and a row would be marital status or the other way around, and it's easier to present the information of two kinds of qualitative pieces of data in a table rather than a carafe of bomb use it and then the third bullet here on one tennis uses scatter diagram when both of the variables are quantitative, for example, the example he is here the distance from C. Sun versus the duration of time to reach see some because the distance might be say 1011 1213 miles and the time might be for 30 minutes, 45 minutes 52.5 minutes eccentric search or so in both the variables are quantitative nature or interval or ratio variables use things like scatter diagram are sometimes called the scatter plot to than the last slide 111 is about hypothesis testing and confidence are walls as they relate to the disk difference between qualitative and quantitative. We use qualitative data when it's a proportion, which means it's a ratio of something and a quark of a example of a quantitative piece of information is the mean because the mean is a calculation of other quantitative data, and and that's it for top 10 concept number 10